Translate skill docs (article-deep-summary, llm-summary-review, keyword-cleanup-review) from English to Chinese
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---
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name: keyword-cleanup-review
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description: Review and curate this repository's daily keyword index and frequency stats. Use when the user wants to inspect `data/term_index/term_stats.json`, recent `data/term_index/daily/*.json`, `configs/term_aliases.json`, `configs/term_stopwords.json`, or `configs/filter_context.personal.json` to propose alias merges, stopwords, watch terms, or `interest_keywords` updates without directly modifying configs.
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description: 审查和整理本仓库的每日关键词索引和频率统计。当用户需要检查 `data/term_index/term_stats.json`、最近的 `data/term_index/daily/*.json`、`configs/term_aliases.json`、`configs/term_stopwords.json` 或 `configs/filter_context.personal.json`，以提议别名合并、停用词、关注词或 `interest_keywords` 更新（但不直接修改配置）时使用。
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---
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# Keyword Cleanup Review
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# 关键词清理审查
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Use this skill to turn the repository's keyword statistics into reviewable cleanup suggestions.
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使用此技能将仓库的关键词统计转化为可审查的清理建议。
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## Workflow
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## 工作流程
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1. Build a compact review bundle:
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1. 构建精简的审查数据包：
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```bash
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python skills/keyword-cleanup-review/scripts/build_review_bundle.py
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```
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Optional knobs:
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可选参数：
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- `--days 7`
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- `--top 50`
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- `--output outputs/term_index/review/keyword-cleanup-bundle.json`
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2. Read the generated bundle and the suggestion schema:
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2. 阅读生成的数据包和建议模式：
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- `outputs/term_index/review/keyword-cleanup-bundle.json`
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- `skills/keyword-cleanup-review/references/suggestion-schema.md`
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3. Produce two outputs:
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3. 生成两份输出：
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- A short Markdown review for humans
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- A JSON suggestion file matching the schema
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- 一份简短的供人工审阅的 Markdown 报告
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- 一份符合模式的 JSON 建议文件
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4. Keep the boundary strict:
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4. 严格保持边界：
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- Suggest changes to `configs/term_aliases.json`
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- Suggest changes to `configs/term_stopwords.json`
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- Suggest additions to `configs/filter_context.personal.json`
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- Do not directly edit these files unless the user explicitly asks
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- Do not suggest direct edits to `configs/filter_rules.json` unless the user asks for rule logic changes
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- 建议 `configs/term_aliases.json` 的修改
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- 建议 `configs/term_stopwords.json` 的修改
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- 建议 `configs/filter_context.personal.json` 的新增
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- 除非用户明确要求，否则不要直接编辑这些文件
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- 除非用户要求修改规则逻辑，否则不要建议直接编辑 `configs/filter_rules.json`
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## Review Heuristics
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## 审查启发式规则
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Prioritize these decisions:
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优先考虑以下决策：
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- Alias suggestion
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- Same concept with different naming, casing, abbreviation, or Chinese/English variants
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- Stopword suggestion
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- Too generic, too broad, or too noisy to help filtering
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- Interest keyword suggestion
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- High-frequency and aligned with the user's backend engineering, AI-agent, and frontier-tech focus
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- Watch term
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- Recent and potentially important, but evidence is still weak
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- 别名建议
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- 同一概念的不同命名、大小写、缩写或中英文变体
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- 停用词建议
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- 过于通用、过于宽泛或噪声过大，对过滤无帮助
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- 兴趣关键词建议
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- 高频且与用户的后端工程、AI Agent 和前沿技术关注方向一致
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- 关注词
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- 近期出现且可能重要，但证据尚不充分
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Prefer conservative suggestions. If confidence is low, put the term into `watch_terms`.
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建议保守为主。如果置信度较低，将词放入 `watch_terms`。
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## Inputs
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## 输入
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Primary inputs:
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主要输入：
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- `data/term_index/term_stats.json`
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- `data/term_index/daily/*.json`
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@@ -67,36 +67,36 @@ Primary inputs:
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- `configs/term_watchlist.json`
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- `configs/term_change_log.json`
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The bundled script already compacts these into a single review bundle.
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打包脚本已将这些内容压缩为单个审查数据包。
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## Output Expectations
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## 输出要求
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The Markdown output should:
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Markdown 输出应：
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- Summarize the current state briefly
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- List the top terms worth acting on
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- Separate alias, stopword, interest-keyword, and watch-term recommendations
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- Explain reasoning in short, concrete sentences
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- 简要总结当前状态
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- 列出值得处理的高频词
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- 分类别名、停用词、兴趣关键词和关注词建议
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- 用简短、具体的句子解释理由
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The JSON output should follow:
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JSON 输出应遵循：
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- `references/suggestion-schema.md`
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## Repository Notes
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## 仓库说明
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Current repository behavior:
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当前仓库行为：
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- Keyword stats are program-maintained, not LLM-maintained
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- Stats are built from `keywords`, not `topics`
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- Stats only include non-`drop` candidates
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- `data/term_index/term_stats.json` is rebuilt from daily files, so reruns overwrite the same day instead of double-counting
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- cleanup policy, watchlist, and change log are repository-managed governance inputs and should be respected during review
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- 关键词统计由程序维护，而非 LLM 维护
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- 统计基于 `keywords` 构建，而非 `topics`
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- 统计仅包含非 `drop` 候选项
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- `data/term_index/term_stats.json` 从每日文件重建，因此重新运行会覆盖同一天的数据而非重复计算
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- 清理策略、关注列表和变更日志是仓库管理的治理输入，审查时应予以尊重
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Keep suggestions aligned with that design.
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保持建议与此设计保持一致。
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## Resources
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## 资源
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- Script:
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- 脚本：
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- `scripts/build_review_bundle.py`
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- Reference:
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- 参考文档：
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- `references/suggestion-schema.md`
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